An analysis of the relationship between donor and recipient biomarkers and kidney graft function, dysfunction, and rejection

被引:2
|
作者
Mao, Yi-Jie [1 ]
Xu, Dong-Sheng [1 ]
Liu, Shuang-De [1 ]
Yan, Jie-Ke [1 ]
Liu, Xiao-Li [1 ]
Zhang, Xu-Feng [1 ]
Pan, Wen-Gu [1 ]
Tian, Chuan [1 ]
机构
[1] Shandong Univ, Hosp 2, Multidisciplinary Innovat Ctr Nephrol, Dept Kidney Transplantat, 247 Beiyuan Rd, Jinan 250000, Peoples R China
关键词
Biomarkers; Reduced graft function; Predictive value; Kidney transplantation; Dysfunction; Rejection; GELATINASE-ASSOCIATED LIPOCALIN; URINARY BIOMARKERS; ALLOGRAFT OUTCOMES; INJURY MOLECULE-1; SLOW; RECOVERY; SURVIVAL; DIALYSIS; POSTTRANSPLANT; PREDICTORS;
D O I
10.1016/j.trim.2023.101934
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
Background: The study aimed to find predictive biomarkers to evaluate donor kidney function to predict graft dysfunction as well as to assess an early signs of acute graft rejection.Method: Twenty-seven deceased donors and 54 recipients who underwent a successful kidney transplantation were enrolled in the study. An assessment was made in serum and urine from donors and recipients to measure the following biomarkers: neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule-1 (KIM-1), tissue inhibitor of metalloproteinase 2 (TIMP-2) and urinary N-acetyl-b-D-glucosaminidase (uNAG). These bio-markers were used to establish a model for predicting a reduced graft function (RGF) classified as either a delayed or slow graft function.Result: Our analysis suggest that out of four tested biomarkers, the serum TIMP-2 and uNAG levels of the donors had a predictive value for RGF; the area under the receiver operating characteristic curves (AUROC) of serum TIMP-2 and uNAG were 0.714 and 0.779, respectively. The combined best fitting prediction model of serum TIMP-2, uNAG, and creatinine levels was better in predicting RGF than the serum creatinine level alone. In addition, the recipient serum TIMP-2 level on the third day post-transplantation (D3) was associated with the estimated glomerular filtration rate (eGFR) on the seventh day post-transplantation (D7; OR 1.119, 95% CI 1.016-1.233, p = 0.022). Furthermore, the ROC curve value revealed that the AUROC of TIMP-2 on D3 was 0.99 (95% CI 0.97-1, p < 0.001), and this was the best predictive value of the renal function on D7.Conclusions: Donor serum TIMP-2 and uNAG levels are useful predictive biomarkers because they can provide the donor-based prediction for RGF.
引用
收藏
页数:7
相关论文
共 50 条
  • [1] Deceased Kidney Donor Biomarkers: Relationship between Delayed Kidney Function and Graft Function Three Years after Transplantation
    Maslauskiene, Rima
    Vaiciuniene, Ruta
    Tretjakovs, Peteris
    Gersone, Gita
    Radzeviciene, Aurelija
    Bura, Andrejus
    Stankevicius, Edgaras
    Bumblyte, Inga Arune
    DIAGNOSTICS, 2024, 14 (07)
  • [2] A pair analysis of the delayed graft function in kidney recipient: The critical role of the donor
    Robert, Rene
    Guilhot, Joelle
    Pinsard, Michel
    Longeard, Pol-Louis
    Jacob, Jean-Paul
    Gissot, Valerie
    Hauet, Thierry
    Seguin, Francois
    JOURNAL OF CRITICAL CARE, 2010, 25 (04) : 582 - 590
  • [3] Donor Kidney Volume and Its Effect on Recipient Graft Function
    Diez, A.
    Goggins, W.
    Powelson, J.
    Taber, T.
    Yaqub, M. S.
    Mishler, D.
    Sundaram, C.
    Mujtaba, M. A.
    Perry, T.
    Ping, S.
    Sharfuddin, A. A.
    AMERICAN JOURNAL OF TRANSPLANTATION, 2012, 12 : 329 - 330
  • [4] Living donor postnephrectomy kidney function and recipient graft loss: A dose-response relationship
    Holscher, Courtenay M.
    Ishaque, Tanveen
    Wang, Jacqueline M. Garonzik
    Haugen, Christine E.
    DiBrito, Sandra R.
    Jackson, Kyle R.
    Muzaale, Abimereki D.
    Massie, Allan B.
    Al Ammary, Fawaz
    Ottman, Shane E.
    Henderson, Macey L.
    Segev, Dorry L.
    AMERICAN JOURNAL OF TRANSPLANTATION, 2018, 18 (11) : 2804 - 2810
  • [5] ACCELERATION OF GRAFT REJECTION BY PRETREATMENT OF GRAFT DONOR WITH RECIPIENT CELLS (DONOR SENSITIZATION)
    HARRIS, NS
    VANALTEN, PJ
    CELLULAR IMMUNOLOGY, 1974, 11 (1-3) : 342 - 353
  • [6] Ratio of donor kidney weight to recipient bodyweight as an index of graft function
    Kim, YS
    Moon, JI
    Kim, DK
    Kim, SI
    Park, K
    LANCET, 2001, 357 (9263): : 1180 - 1181
  • [7] Optimizing living donor kidney graft function by donor-recipient pair selection
    Brennan, Todd V.
    Bostrom, Alan
    Feng, Sandy
    TRANSPLANTATION, 2006, 82 (05) : 651 - 656
  • [8] Relationship between Living Kidney Donor Follow-Up GFR and Recipient Graft Loss.
    Holscher, C.
    Ishaque, T.
    Haugen, C.
    DiBrito, S.
    Jackson, K.
    Muzaale, A.
    Massie, A.
    Henderson, M.
    Wang, J. Garonzik
    Segev, D.
    AMERICAN JOURNAL OF TRANSPLANTATION, 2018, 18 : 334 - 335
  • [9] Effect of the similarity of gut microbiota composition between donor and recipient on graft function after living donor kidney transplantation
    Ji Eun Kim
    Hyo-Eun Kim
    Hyunjeong Cho
    Ji In Park
    Min-Jung Kwak
    Byung-Yong Kim
    Seung Hee Yang
    Jung Pyo Lee
    Dong Ki Kim
    Kwon Wook Joo
    Yon Su Kim
    Bong-Soo Kim
    Hajeong Lee
    Scientific Reports, 10
  • [10] Effect of the similarity of gut microbiota composition between donor and recipient on graft function after living donor kidney transplantation
    Kim, Ji Eun
    Kim, Hyo-Eun
    Cho, Hyunjeong
    Park, Ji In
    Kwak, Min-Jung
    Kim, Byung-Yong
    Yang, Seung Hee
    Lee, Jung Pyo
    Kim, Dong Ki
    Joo, Kwon Wook
    Kim, Yon Su
    Kim, Bong-Soo
    Lee, Hajeong
    SCIENTIFIC REPORTS, 2020, 10 (01)